Abstract

A comprehensive statistical analysis of creep data is a difficult task because there are many layers of uncertainty for a given dataset. Sources of uncertainty are inherent in both the databases that provide data, and the data themselves. Additionally, creep rupture predictions made with time-temperature parameter (TTP) models add an additional layer of uncertainty due to the fundamentally different ways in which each TTP model predicts creep behavior. A set of guidelines from the ECCC currently exist for such analyses, but they are best suited for narrowly-defined datasets. In this study, a broader set of guidelines are developed to analyze a large database of creep rupture data using the Larson-Miller Parameter. The guidelines are applied to a dataset of 316 stainless steel, which is collected across multiple public and private databases. The properties of the dataset are analyzed by comparing its statistical properties to that of the full dataset to subsets of form, thermomechanical processing, and chemistry metadata. The predictive ability of eight TTP models is analyzed by running nine combinations of isotherm and data culling conditions through each model. Recommendations are made in expanding the breadth of these guidelines. Acquiring the necessary creep rupture data to perform such a large analysis is time- and energy-expensive. Depending on the design specifications of a component, creep rupture can take anywhere between 10,000 to over 300,000 hours to occur. An accelerated creep test that accurately predicts the creep deformation and life of metallic materials is desired. This study also proposes modifying the Stepped Isostress Method designed for polymers to work for metallic materials in general. Experimental evidence is provided using 304SS subjected to 600°C. Monotonic tensile and conventional creep tests are conducted to establish baseline properties. Stepped Isostress Method tests are conducted and analytically adjusted to produce accelerated creep deformation and rupture data. Recommendations concerning future work on SSM are provided.^